Search engines are used throughout the World Wide Web and Internet, including, but not limited to social networks, general Internet searches, e.g., Google, Yahoo, Bing, etc. . . . , and retail commercial websites. Search engines are also used to manage human resources databases, inventory database, and the like. Such systems typically include the search engine logic, the database, front end logic, and any business or other logic that may be used to present or organize the search engine results.
The data in the database and the logic comprising such systems are almost always constantly improved or updated. Various personalized eCommerce recommender systems, for example, have been developed during the past two decades. However, it is hard to directly apply these recommender systems in the grocery domain. Most of the eCommerce websites focus on durable goods or standardized products, while grocery retailers sell consumables. Moreover, online grocery applications and recommender systems must be personalized because each individual shopper has her own food preferences. Current eCommerce recommender systems are often centered around similar items, whereas grocery systems must be devoted to customers and their preferences. Grocery systems must not only find the type of products consumers like (e.g., bananas, avocados, deli meat), but also must pick the right specific item (green vs. yellow bananas, hard vs. ripe avocados, thick vs. thin sliced deli meat, etc.) for delivery.
Online grocery systems face challenges that are rarely encountered in traditional eCommerce systems. In traditional eCommerce, delivery time can be flexible, from a few days to several weeks. Traditional eCommerce orders do not have the same urgency as grocery orders because they typically contain durable goods, as opposed to consumable (and often perishable) goods in grocery orders. As such, value is the main benefit associated with traditional eCommerce systems. Customers trade off longer wait times for lower prices. The delivery time window for grocery orders, by comparison, is typically two hours. In many cases, people cannot afford to wait longer for their grocery orders. A late order may mean that the customer runs out of food. The main benefit associated with online grocery systems is convenience, since customers can typically get the same products in stores for similar prices. To meet the demands of online grocery customers, a service provider must have an efficient transportation system and a precise demand forecasting and inventory replenishment system.
Unlike in traditional eCommerce systems, the inventory stock status of a grocery product is harder to predict. For instance, an item could be available when a customer places an order, but the same item is out of stock when the order is being fulfilled for delivery. These situations seldom happen in non-grocery eCommerce, where items can be held upon the order placement. Grocery items, on the other hand, typically cannot be held mainly due to freshness concerns.
As a result, it is not uncommon that an item needs to be substituted in a grocery order. Determining how to select substitutions for each customer presents unique challenges. A bad substitution can negate the benefit (i.e., convenience) of online grocery shopping, as the customer may have to go to the store to purchase the original item if the chosen substitution does not fit her needs. A common approach is to compute a similar-item list for each item. If an item is out of stock, the most similar item candidates in its similar-item list are suggested for substitution. The similarity between two items can be determined as a weighted combination of multiple features: the item's name, category, brand, size, and so on. For each customer, those weights can be tuned differently. For example, a customer for whom brand is more important than size would have brand weighted more heavily so that she is more likely to receive a substitute item from the same brand but in a different size. Meanwhile, another customer might receive a same-size package but from a different brand if the size is more important to her.
In addition, online grocery shopping using recipe websites presents distinct challenges. It is difficult for consumers to efficiently locate the correct grocery items that correspond to ingredients listed in recipes. With current solutions, a customer may go to retailer's website after visiting a recipe website to find each ingredient separately and create a shopping list. Alternatively, a customer may print the recipe and shop for each ingredient in a brick-and-mortar grocery store. Both solutions require users to manually map an ingredient to a product in a grocery store, which is time-consuming, frustrating, and prone to error.
The present invention is aimed at one or more of the problems identified above.